nuster1128 / Awesome-Causal-Papers
We organize papers related to causal that published on top conferences recently. (因果领域论文分类汇总)
☆56Updated last year
Related projects: ⓘ
- Official code of "Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting" (2023 ICLR)☆16Updated last year
- ☆21Updated 2 years ago
- ☆39Updated last month
- 关于causal discovery, invariant learning, machine learning等方向的论文阅读笔记和slides总结☆23Updated 8 months ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆16Updated last year
- ☆41Updated 7 months ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆76Updated 10 months ago
- The official implementation for "Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment" which is accepted to NeurIP…☆22Updated 4 months ago
- A list of Graph Causal Learning materials.☆178Updated 5 months ago
- ☆22Updated last year
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆70Updated 3 years ago
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆16Updated last month
- Official Implementation of Information Theoretic Counterfactual Learning from Missing Not At Random Feedback. NeurIPS 2020.☆27Updated 3 years ago
- Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)☆114Updated last year
- This repository collects recent top papers about causal inference for recommendation. We will keep updating the paper list weekly.☆15Updated 2 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆30Updated 2 years ago
- Paper lists for Temporal Point Process☆97Updated 2 weeks ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆97Updated last year
- Papers about out-of-distribution generalization on graphs.☆149Updated last year
- ☆17Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆80Updated last year
- ☆37Updated 5 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆25Updated 2 years ago
- ☆19Updated 2 years ago
- An index of causal inference based recommendation algorithms (TOIS).☆46Updated 6 months ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆13Updated 10 months ago
- Pytorch Implementation for paper "Adversarial Graph Disentanglement"☆12Updated last year
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆25Updated 2 years ago
- Schedule for learning on graphs seminar☆110Updated last year
- Causal Representation Learning for Out-of-Distribution Recommendation (WWW'22)☆14Updated 8 months ago